// Copyright 2017 The Draco Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
#ifndef DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_GEOMETRIC_NORMAL_PREDICTOR_AREA_H_
#define DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_GEOMETRIC_NORMAL_PREDICTOR_AREA_H_

#include "draco/compression/attributes/prediction_schemes/mesh_prediction_scheme_geometric_normal_predictor_base.h"

namespace draco {

// This predictor estimates the normal via the surrounding triangles of the
// given corner. Triangles are weighted according to their area.
template <typename DataTypeT, class TransformT, class MeshDataT>
class MeshPredictionSchemeGeometricNormalPredictorArea
    : public MeshPredictionSchemeGeometricNormalPredictorBase<
      DataTypeT, TransformT, MeshDataT> {
    typedef MeshPredictionSchemeGeometricNormalPredictorBase<
    DataTypeT, TransformT, MeshDataT>
    Base;

  public:
    explicit MeshPredictionSchemeGeometricNormalPredictorArea(const MeshDataT &md)
        : Base(md) {
        this->SetNormalPredictionMode(TRIANGLE_AREA);
    };
    virtual ~MeshPredictionSchemeGeometricNormalPredictorArea() {}

    // Computes predicted octahedral coordinates on a given corner.
    void ComputePredictedValue(CornerIndex corner_id,
                               DataTypeT *prediction) override {
        DRACO_DCHECK(this->IsInitialized());
        typedef typename MeshDataT::CornerTable CornerTable;
        const CornerTable *const corner_table = this->mesh_data_.corner_table();
        // Going to compute the predicted normal from the surrounding triangles
        // according to the connectivity of the given corner table.
        VertexCornersIterator<CornerTable> cit(corner_table, corner_id);
        // Position of central vertex does not change in loop.
        const VectorD<int64_t, 3> pos_cent = this->GetPositionForCorner(corner_id);
        // Computing normals for triangles and adding them up.

        VectorD<int64_t, 3> normal;
        CornerIndex c_next, c_prev;
        while (!cit.End()) {
            // Getting corners.
            if (this->normal_prediction_mode_ == ONE_TRIANGLE) {
                c_next = corner_table->Next(corner_id);
                c_prev = corner_table->Previous(corner_id);
            } else {
                c_next = corner_table->Next(cit.Corner());
                c_prev = corner_table->Previous(cit.Corner());
            }
            const VectorD<int64_t, 3> pos_next = this->GetPositionForCorner(c_next);
            const VectorD<int64_t, 3> pos_prev = this->GetPositionForCorner(c_prev);

            // Computing delta vectors to next and prev.
            const VectorD<int64_t, 3> delta_next = pos_next - pos_cent;
            const VectorD<int64_t, 3> delta_prev = pos_prev - pos_cent;

            // Computing cross product.
            const VectorD<int64_t, 3> cross = CrossProduct(delta_next, delta_prev);
            normal = normal + cross;
            cit.Next();
        }

        // Convert to int32_t, make sure entries are not too large.
        constexpr int64_t upper_bound = 1 << 29;
        if (this->normal_prediction_mode_ == ONE_TRIANGLE) {
            const int32_t abs_sum = normal.AbsSum();
            if (abs_sum > upper_bound) {
                const int64_t quotient = abs_sum / upper_bound;
                normal = normal / quotient;
            }
        } else {
            const int64_t abs_sum = normal.AbsSum();
            if (abs_sum > upper_bound) {
                const int64_t quotient = abs_sum / upper_bound;
                normal = normal / quotient;
            }
        }
        DRACO_DCHECK_LE(normal.AbsSum(), upper_bound);
        prediction[0] = static_cast<int32_t>(normal[0]);
        prediction[1] = static_cast<int32_t>(normal[1]);
        prediction[2] = static_cast<int32_t>(normal[2]);
    }
    bool SetNormalPredictionMode(NormalPredictionMode mode) override {
        if (mode == ONE_TRIANGLE) {
            this->normal_prediction_mode_ = mode;
            return true;
        } else if (mode == TRIANGLE_AREA) {
            this->normal_prediction_mode_ = mode;
            return true;
        }
        return false;
    }
};

}  // namespace draco

#endif  // DRACO_COMPRESSION_ATTRIBUTES_PREDICTION_SCHEMES_MESH_PREDICTION_SCHEME_GEOMETRIC_NORMAL_PREDICTOR_AREA_H_
